Gumstix Scholarly Articles

Kenny Akers is a rising senior student at Woodside Priory High School in Portola Valley California and 3-year veteran of the FIRST Robotics Competition — An international contest of wits to see which team of High School students can custom-build a robot to complete a complex task. When Gumstix released the Aerocore 2 for NVIDIA Jetson we called upon his experience, skill, and enthusiasm to demonstrate its potential in robotics and automation. He aims to demonstrate its ability to drive autonomous problem solving in robotics through computer vision and deep learning.

Steam Bot Willie, Team 751’s 2017 submission for the FIRST robotics competition

Kenny is your average high school kid, enjoying running, music and hanging out with his friends, but he is also a self-professed, self-taught tinkerer and software developer. His interest in Arduino, C++, and Raspberry Pi eventually led him to us, and he promptly got himself a seat at the table. Now he is interning here for the second consecutive summer and applying his skills to the Aerocore 2 for Jetson. “I knew about the Jetson platform through the FIRST competition, where a few teams [were] using it for computer vision,” he shared, “Coupled with TensorRT and NVIDIA’s support for AI applications, the Jetson is the optimal platform for my purposes.”

Kenny’s Aerocore 2 wired up for test

Diving headlong into deep learning, Kenny has already brought up a convolutional neural network, using TensorFlow as the backbone, that uses our Caspa HD camera module and the Aerocore 2 for NVIDIA Jetson to identify and classify up to 80 objects concurrently, and in real-time.

His goal is to demonstrate the capabilities of the NVIDIA Jetson TX2, coupled with the Aerocore 2 platform, to his team and incorporate it into their design for this year’s FIRST robotics challenge, so he has set aside the object classification for now to work on interpreting the AI’s output and translating it into robotic actions. As a proof of concept, he hopes to have an iRobot Create 2 navigate to an object of specific class and interact with it, which at this point could be as simple as turning on an LED.

Early demo of Kenny’s progress with OpenCV and TensorFlow on Aerocore 2 for Jetson

He won’t find out until January what his challenge will be, and then he and his team will have 6 weeks to fund, design, program, and test his bot before the competition begins in earnest. His work this summer, he hopes, will be helpful in improving the design’s autonomous performance at the competition.

Developing on the Jetson has proven to be far more agreeable than he had initially expected. “Besides a few technicalities with configuring library backends and getting a sufficient camera stream, I was surprised by the relatively low amount of hurdles I encountered compared to other embedded systems,” he confessed. NVIDIA has done a great job of documenting and supporting the Jetson TX series compute modules and has made the lives of developers of varying skill the better for it.

Working with Aerocore 2, a Geppetto-designed board, has left a good impression on this high school self-starter. “I think Gumstix offers a level of customizability in the field of embedded computing that I am yet to see by other entities. Especially with Geppetto, the ability for a client to tailor a design to their application is very useful.”

Kenny is the first, and definitely not the last, to employ the Aerocore 2 for NVIDIA Jetson for combining edge AI and robotics. And there is no reason to stop there. In the past, Geppetto and Geppetto-designed boards have been used by Yale undergrads to teach grade school students the fundamentals of computers.

Gumstix is lucky and grateful to have Kenny here working with NVIDIA Jetson and we are excited to see what he does with the Aerocore 2 for Jetson. Gumstix will be following his progress enthusiastically as he and his team take on the FIRST Robotics Challenge in January.

Gumstix Caspa VL camera onboard to snap history

NASA set a new distance record for CubeSats this May when a pair of CubeSats called Mars Cube One (MarCO) reached 621,371 miles (1 million kilometers) from Earth. One of the CubeSats, called MarCO-B used a Gumstix Caspa VL fisheye camera to snap its first photo on May 9, 2018. That photo is part of the process used by the engineering team to confirm the spacecraft’s high-gain antenna has properly unfolded.

Photo Caption: The first image captured with Gumstix Caspa VL camera by NASA’s Mars Cube One (MarCO) CubeSats. The image, which shows both the CubeSat’s unfolded high-gain antenna at right and the Earth and its moon in the center, was acquired by MarCO-B on May 9. Image Credit: NASA/JPL-Caltech

The MarCO spacecraft including the Gumstix Overo IronSTORM-Y are the first CubeSats ever launched to deep space. Most never go beyond Earth orbit; they generally stay below 497 miles (800 kilometers) above the planet. Though they were originally developed to teach university students about satellites, CubeSats are now a major commercial technology, providing data on everything from shipping routes to environmental changes.

If the MarCO CubeSats make the entire journey to Mars, they will attempt to relay data about InSight back to Earth as the lander enters the Martian atmosphere and lands. MarCO will not collect any science, but are intended purely as a technology demonstration. They could serve as a pathfinder for future CubeSat missions.

The MarCO and InSight projects are managed for NASA’s Science Mission Directorate, Washington, by JPL, a division of the California Institute of Technology, Pasadena.

Yale undergraduates bring computer architecture and design into the high school classroom with a unique approach to STEM.

Today, kids can usually pick up any device and start using it right away. But to them, the inner workings of computers may be a complete mystery. Jacob Marks, a Yale senior and president of the Ventures in Science at Yale (ViS) student organization, along with his colleagues designed the “It’s a Processor” lesson plan to help students demystify computer hardware. Analogies and demonstrations help illustrate how all of the hardware components in a computer come together to perform computational tasks.

Search and Rescue

Jin Q. Cui et al, at the National University of Singapore, have used the Overo FIRESTORM COM to build drones that can be used for search and rescue missions in post-disaster situations. Check out their 2016 paper in Unmanned Systems.

Date Added: 04/15/2016.

Low-Cost Swarming

A group of electrical engineers at the Czech Technical University in Prague have recently employed Overo COMs and the Caspa Camera modules in their lost-cost swarming project. Check out Jan Faigl, Tomáš Krajník, Jan Chudoba and Martin Saska’s 2013 paper in theIEEE International Conference on Robotics and Automation. Learn more about how Gumstix supports UAV and MAV research at our blog.

Gumstix has a new webpage dedicated to academic research projects and patents!

We want researchers and innovators to know what Gumstix can do for them, especially when it comes to constructing the medical, scientific and industrial devices populating the “Internet of Things”. Aside from learning about how Gumstix expansion boards, single board computers and computers-on-modules (COMs) can be used for research in machine learning or UAV prototypes, researchers can learn more about Gumstix’s expansion boards for third-party COMs, including the Raspberry Pi Compute Module here.

Keep up to date with the latest patents and research projects that use Gumstix products at the Gumstix Scholar News section of the website.

We want to hear from you. How have Gumstix products help streamline your research project? Share your projects with us @ communications@gumstix.com